skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: 3D models of the Leader Valley using satellite & UAV imagery following the 2016 Kaikoura earthquake
The ability to quickly, efficiently and reliably characterize changes in the landscape following an earthquake has remained a challenge for the earthquake engineering profession. The 2016 Mw7.8 Kaikoura earthquake provided a unique opportunity to document changes in topography following an earthquake on a regional scale using satellite derived high-resolution digital models. Along-track stereo satellite imagery had been collected for the pre-event topography. Satellites were tasked and collected stereo-mode post-event imagery. Both sets of images were used to create digital surface models (DSMs) of the affected area before and after the event. The procedure followed and indicative results for the Leader valley are presented with emphasis on the challenges associated with the implementation of the technique for the first time in this environment. The valley is of interest because of the variety of features it includes, i.e., the large Leader landslide, smaller landslides, stable sloping and flat ground as well as fault rupture lineaments. The open-source SETSM software is used to provide multiple DSMs. Our workflow is described and results are compared against the DSM created using Structure-from-Motion with imagery collected by Unmanned Aerial Vehicles (UAV) and aerial LIDAR. Overall, the sub-meter agreement between the DSM created using satellites and the DSM created using UAV and LIDAR datasets demonstrates viability for use in seismic studies, but features smaller than about 0.5 m are more difficult to discern.  more » « less
Award ID(s):
1719496
PAR ID:
10149619
Author(s) / Creator(s):
Date Published:
Journal Name:
11th US National Conference on Earthquake Engineering
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. (, 11th US National Conference on Earthquake Engineering)
    Following the November 14 2016 Mw7.8 Kaikoura earthquake, field expeditions were undertaken using Unmanned Aerial Vehicles (UAVs) to map 25 sites of scientific interest with a plan area of 7.2 km2. A total of 23,172 images collected by the UAVs were used as input in Structure-from-Motion (SfM) to create 3D models of the target areas with a focus on landslides and fault rupture. Two sites are presented in more detail as examples of the data generated; a section of the Kekerengu fault that ruptured during the earthquake, and the Limestone Hills landslide. The sites were mapped at high resolution with ground sampling distance that varied from 0.5 to 7.0 cm/pixel. The developed SfM models were compared to 1-m aerial LiDAR data and the results were found to be comparable. However, the higher resolution of the SfM digital surface model (DSM), paired with the imagery facilitated more detailed interpretations, highlighting the usefulness of the UAV-enabled SfM as a mobile and effective technique for documenting perishable post-earthquake reconnaissance data. 
    more » « less
  2. ; ; ; (, Drones)
    High resolution mapping of coastal habitats is invaluable for resource inventory, change detection, and inventory of aquaculture applications. However, coastal areas, especially the interior of mangroves, are often difficult to access. An Unmanned Aerial Vehicle (UAV), equipped with a multispectral sensor, affords an opportunity to improve upon satellite imagery for coastal management because of the very high spatial resolution, multispectral capability, and opportunity to collect real-time observations. Despite the recent and rapid development of UAV mapping applications, few articles have quantitatively compared how much improvement there is of UAV multispectral mapping methods compared to more conventional remote sensing data such as satellite imagery. The objective of this paper is to quantitatively demonstrate the improvements of a multispectral UAV mapping technique for higher resolution images used for advanced mapping and assessing coastal land cover. We performed multispectral UAV mapping fieldwork trials over Indian River Lagoon along the central Atlantic coast of Florida. Ground Control Points (GCPs) were collected to generate a rigorous geo-referenced dataset of UAV imagery and support comparison to geo-referenced satellite and aerial imagery. Multi-spectral satellite imagery (Sentinel-2) was also acquired to map land cover for the same region. NDVI and object-oriented classification methods were used for comparison between UAV and satellite mapping capabilities. Compared with aerial images acquired from Florida Department of Environmental Protection, the UAV multi-spectral mapping method used in this study provided advanced information of the physical conditions of the study area, an improved land feature delineation, and a significantly better mapping product than satellite imagery with coarser resolution. The study demonstrates a replicable UAV multi-spectral mapping method useful for study sites that lack high quality data. 
    more » « less
  3. (, Arctic Data Center)
    Arctic landscapes are rapidly changing with climate warming. Vegetation communities are restructuring, which in turn impacts wildlife, permafrost, carbon cycling and climate feedbacks. Accurately monitoring vegetation change is thus crucial, but notable mismatches in scale occur between current field and satellite-based monitoring. Remote sensing from unmanned aerial vehicles (UAVs) has emerged as a bridge between field data and satellite imagery mapping. In this work we assess the viability of using high resolution UAV imagery (RGB and multispectral), along with UAV derived Structure from Motion (SfM) to predict cover, height and above-ground biomass of common Arctic plant functional types (PFTs) across a wide range of vegetation community types. We collected field data and UAV imagery from 45 sites across Alaska and northwest Canada. We then classified UAV imagery by PFT, estimated cover and height, and modeled biomass from UAV-derived volume estimates. Here we present datasets summarizing this data. 
    more » « less
  4. ; (, NSF Arctic Data Center)
    Delineations of Retrogressive Thaw Slump (RTS) expansion and light detection and ranging (LiDAR) datasets (LAS files) of RTS sites were used to model how rates of RTS change are influenced by topographic and climatic characteristics across northern Alaska. LiDAR data were collected at ten sites, where five were collected from an uncrewed aerial system (UAS) and five were collected from a terrestrial LiDAR systems (TLS). LiDAR datasets were used to bias correct the open-source ArcticDEM (2 meter-resolution) for calculating annual rates of RTS volumetric losses across all sites. RTS Delineations were used to calculate annual rates of RTS areal expansion and summarize topographic characteristics calculated from the corrected ArcticDEM. Two shapefiles were created from historic satellite and aerial imagery (1949-2021) to summarize RTS areal change across 44 slumps: AK_RTS_ExansionDelineations.shp summarizes the area of RTS expansion between two time periods and AK_RTS_Delineations.shp summarizes the total RTS outline in each year where RTS expansion occurs. LiDAR UAS and TLS data are provided as LAS files from 12 slumps (five sites) near Toolik Lake and 9 slumps (5 sites) within the Noatak National Preserve. 
    more » « less
  5. ; ; ; ; ; ; ; (, Hydroshare)
    The data were collected in the Helambu region of central Nepal as part of the "Nepal-FRES" (Frontier Research in Earth Sciences) project to document the impacts of the 2021 Melamchi Flood, aiming to understand its cascading nature, the legacy of the 2015 Gorkha earthquake, and fluvial adjustment to such an extreme sediment transporting event. Polygon KML files of landslides, active river channels, and river terraces were mapped using 50 cm-resolution pre- and post-event Pléiades stereo satellite imagery. This data package comprises:  Melamchi Khola Catchment (study area)  Landslides before the 2015 Gorkha earthquake, between 2015 and 2020, between Nov 2020 and Oct 2021 (Melamchi Flood), and between Oct 2021 and Dec 2023  Obscured areas in which landslide mapping is incomplete due to the existence of clouds and shadow  River channel of Melamchi Khola in Nov 2020 and Oct 2021 (w/ the thalweg line in Oct 2021)  River terraces in Oct 2021  Forested areas in Nov 2020 and Dec 2023 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email